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Informatics for Perinatal and Neonatal Research

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Book cover Pediatric Biomedical Informatics

Part of the book series: Translational Bioinformatics ((TRBIO,volume 10))

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Abstract

Effective biomedical informatics applications supporting newborn populations must go beyond simply adapting data systems or decision support tools designed for adult or even pediatric patient care. Within the neonatal intensive care unit (NICU), additional precision is required in the measurement of data elements such as age and weight where day-to-day changes may be clinically relevant. Data integration is also critical as vital information including the infant’s gestational age and maternal medical history originate from the mother’s medical chart or prenatal records. Access to these relevant data may be limited by barriers between institutions where care was provided, the transition between types of care providers (obstetrics to neonatology), appropriate privacy concerns, and the absence or unreliability of traditional identifiers used in linking records such as name and social security number. We explore challenges unique to the newborn population and review applications of biomedical informatics which have enhanced neonatal and perinatal care processes and enabled innovative research.

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References

  • Addison K, et al. Heart rate characteristics and neurodevelopmental outcome in very low birth weight infants. J Perinatol. 2009;29(11):750–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Allen MC, et al. The limit of viability – neonatal outcome of infants born at 22 to 25 weeks’ gestation. N Engl J Med. 1993;329(22):1597–601.

    Article  CAS  PubMed  Google Scholar 

  • Ananth CV. Menstrual versus clinical estimate of gestational age dating in the United States: temporal trends and variability in indices of perinatal outcomes. Paediatr Perinat Epidemiol. 2007;21 Suppl 2:22–30.

    Article  PubMed  Google Scholar 

  • Baines MA. Excessive infant-mortality; how can it be stayed? A paper contributed to the National Social Science Assn., London meeting. To which is added a short paper, Reprinted from the Lancet [1861] on Infant-Alimentation; or, Artificial Feeding, as a Substitute for Breast-Milk, Considered in Its Physical and Social Aspects. London: Churchill; 1862.

    Google Scholar 

  • Ballard JL, et al. New ballard score, expanded to include extremely premature infants. J Pediatr. 1991;119(3):417–23.

    Article  CAS  PubMed  Google Scholar 

  • Barfield WD, et al. Using linked data to assess patterns of Early Intervention (Ei) referral among very low birth weight infants. Matern Child Health J. 2008;12(1):24–33.

    Article  PubMed  Google Scholar 

  • Blaxter M. The health of the children : a review of research on the place of health in cycles of disadvantage. Studies in deprivation and disadvantage. London: Heinemann Educational; 1981.

    Google Scholar 

  • Brown P, et al. Variations in faculty assessment of Nicu flowsheet data: implications for electronic data display. Int J Med Inform. 2011;80(7):529–32.

    Article  PubMed  Google Scholar 

  • Caley LM. Using geographic information systems to design population-based interventions. Public Health Nurs. 2004;21(6):547–54.

    Article  PubMed  Google Scholar 

  • Clements KM, et al. Maternal socio-economic and race/ethnic characteristics associated with early intervention participation. Matern Child Health J. 2008;12(6):708–17.

    Article  PubMed  Google Scholar 

  • Conde-Agudelo A, et al. Birth spacing and risk of adverse perinatal outcomes: a meta-analysis. JAMA. 2006;295(15):1809–23.

    Article  CAS  PubMed  Google Scholar 

  • Costakos DT. Of lobsters, electronic medical records, and neonatal total parenteral nutrition. Pediatrics. 2006;117(2):e328–32.

    Article  PubMed  Google Scholar 

  • Cradle Cincinnati. Serving moms in Cincinnati’s west side. 2014. Accessed 2 Mar 2016. Available from: http://www.cradlecincinnati.org/connections-2/.

  • Declercq E, et al. Maternal outcomes associated with planned primary cesarean births compared with planned vaginal births. Obstet Gynecol. 2007;109(3):669–77.

    Article  PubMed  Google Scholar 

  • DeFranco E, et al. Influence of interpregnancy interval on birth timing. BJOG. 2014;121(13):1633–40.

    Article  CAS  PubMed  Google Scholar 

  • DeFranco E, et al. Air pollution and stillbirth risk: exposure to airborne particulate matter during pregnancy is associated with fetal death. PLoS One. 2015;10(3):e0120594.

    Article  PubMed  PubMed Central  Google Scholar 

  • DeFranco E, et al. Exposure to airborne particulate matter during pregnancy is associated with preterm birth: a population-based cohort study. Environ Health. 2016;15(1):6.

    Article  PubMed  PubMed Central  Google Scholar 

  • Drummond WH. Neonatal informatics–dream of a paperless Nicu: Part One: The emergence of neonatal informatics. NeoReviews. 2009;10:e480–e87.

    Article  Google Scholar 

  • Dufendach KR, Lehmann CU. Topics in neonatal informatics: essential functionalities of the neonatal electronic health record. NeoReviews. 2015;16(12):e668–e73.

    Article  Google Scholar 

  • Ellsworth MA, et al. Clinical data needs in the neonatal intensive care unit electronic medical record. BMC Med Inform Decis Mak. 2014;14:92.

    Article  PubMed  PubMed Central  Google Scholar 

  • Emmerson AJ, Roberts SA. Rounding of birth weights in a neonatal intensive care unit over 20 years: an analysis of a large cohort study. BMJ Open. 2013;3(12):e003650.

    Article  PubMed  PubMed Central  Google Scholar 

  • English PB, et al. Changes in the spatial pattern of low birth weight in a Southern California county: the role of individual and neighborhood level factors. Soc Sci Med. 2003;56(10):2073–88.

    Article  PubMed  Google Scholar 

  • Gholinezhadasnefestani S, et al. Assessment of quality of Ecg for accurate estimation of heart rate variability in newborns. Engineering in Medicine and Biology Society (EMBC), 2015 37th annual international conference of the IEEE. IEEE, 2015.

    Google Scholar 

  • Gould JB, et al. Incomplete birth certificates: a risk marker for infant mortality. Am J Public Health. 2002;92(1):79–81.

    Article  PubMed  PubMed Central  Google Scholar 

  • Goyal NK, et al. Association of maternal and community factors with enrollment in home visiting among at-risk, first-time mothers. Am J Public Health. 2014;104 Suppl 1:S144–51.

    Article  PubMed  PubMed Central  Google Scholar 

  • Gray JE, et al. Using digital crumbs from an electronic health record to identify, study and improve health care teams. AMIA Annu Symp Proc. 2011;2011:491–500.

    PubMed  PubMed Central  Google Scholar 

  • Hall ES, et al. Spatial analysis in support of community health intervention strategies. AMIA Annu Symp Proc. 2012;2012:311–20.

    PubMed  PubMed Central  Google Scholar 

  • Hall ES, et al. Integrating public data sets for analysis of maternal airborne environmental exposures and stillbirth. AMIA Annu Symp Proc. 2014a;2014:599–605.

    PubMed  PubMed Central  Google Scholar 

  • Hall ES, et al. Evaluation of gestational age estimate method on the calculation of preterm birth rates. Matern Child Health J. 2014b;18(3):755–62.

    Article  PubMed  Google Scholar 

  • Hall ES, et al. Development of a linked perinatal data resource from state administrative and community-based program data. Matern Child Health J. 2014c;18(1):316–25.

    Article  PubMed  PubMed Central  Google Scholar 

  • Hamilton BE, et al. Births: preliminary data for 2012. Natl Vital Stat Rep. 2013;62(3):1–20.

    Google Scholar 

  • Harrison W, Goodman D. Epidemiologic trends in neonatal intensive care, 2007–2012. JAMA Pediatr. 2015;169(9):855–62.

    Article  PubMed  Google Scholar 

  • HCUP Kids’ Inpatient Database (KID). Healthcare cost and utilization project (Hcup). 2016. Accessed 2 Mar 2016. Available from: www.hcup-us.ahrq.gov/kidoverview.jsp.

  • Hsia DC, et al. Accuracy of diagnostic coding for medicare patients under the prospective-payment system. N Engl J Med. 1988;318(6):352–5.

    Article  CAS  PubMed  Google Scholar 

  • Hum RS, et al. Developing clinical decision support within a commercial electronic health record system to improve antimicrobial prescribing in the neonatal icu. Appl Clin Inform. 2014;5(2):368–87.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Iezzoni LI, et al. Comorbidities, complications, and coding bias. Does the number of diagnosis codes matter in predicting in-hospital mortality? JAMA. 1992;267(16):2197–203.

    Article  CAS  PubMed  Google Scholar 

  • Kahn MG, et al. Building a common pediatric research terminology for accelerating child health research. Pediatrics. 2014;133(3):516–25.

    Article  PubMed  PubMed Central  Google Scholar 

  • Kaltenbach K, et al. Predicting treatment for neonatal abstinence syndrome in infants born to women maintained on opioid agonist medication. Addiction. 2012;107 Suppl 1:45–52.

    Article  PubMed  PubMed Central  Google Scholar 

  • Karlsson BM, et al. Sound and vibration: effects on infants’ heart rate and heart rate variability during neonatal transport. Acta Paediatr. 2012;101(2):148–54.

    Article  PubMed  Google Scholar 

  • Khazaei H, et al. Health informatics for neonatal intensive care units: an analytical modeling perspective. Translational engineering in health and medicine. IEEE J. 2015;3:1–9.

    Google Scholar 

  • Kim SY, et al. Prevalence of adverse pregnancy outcomes, by maternal diabetes status at first and second deliveries, Massachusetts, 1998–2007. Prev Chronic Dis. 2015;12:E218.

    PubMed  PubMed Central  Google Scholar 

  • Kotelchuck M, et al. The mosart database: linking the Sart Cors clinical database to the population-based Massachusetts Pell reproductive public health data system. Matern Child Health J. 2014;18(9):2167–78.

    Article  PubMed  PubMed Central  Google Scholar 

  • Kramer MS, et al. The contribution of mild and moderate preterm birth to infant mortality. Fetal and infant health study group of the Canadian perinatal surveillance system. JAMA. 2000;284(7):843–9.

    Article  CAS  PubMed  Google Scholar 

  • Li Q, et al. Phenotyping for patient safety: algorithm development for electronic health record based automated adverse event and medical error detection in neonatal intensive care. J Am Med Inform Assoc. 2014;21(5):776–84.

    Article  PubMed  PubMed Central  Google Scholar 

  • Li Q, et al. Automated detection of medication administration errors in neonatal intensive care. J Biomed Inform. 2015;57:124–133.

    Google Scholar 

  • Longhurst C, et al. Development of a web-based decision support tool to increase use of neonatal hyperbilirubinemia guidelines. Jt Comm J Qual Patient Saf. 2009;35(5):256–62.

    PubMed  Google Scholar 

  • Macdorman MF, Mathews TJ. Recent trends in infant mortality in the United States. NCHS Data Brief. 2008;9:1–8.

    PubMed  Google Scholar 

  • Malloy MH. Prematurity and sudden infant death syndrome: United States 2005–2007. J Perinatol. 2013;33(6):470–5.

    Article  CAS  PubMed  Google Scholar 

  • Manning SE, et al. Early diagnoses of autism spectrum disorders in Massachusetts birth cohorts, 2001–2005. Pediatrics. 2011;127(6):1043–51.

    Article  PubMed  Google Scholar 

  • Martin JA, et al. Births: final data for 2001. Natl Vital Stat Rep. 2002;51(2):1–102.

    PubMed  Google Scholar 

  • Martin JA, et al. Measuring gestational age in vital statistics data: transitioning to the obstetric estimate. Natl Vital Stat Rep. 2015;64(5):1–20.

    Google Scholar 

  • McCabe ER, et al. Fighting for the next generation: Us prematurity in 2030. Pediatrics. 2014;134(6):1193–9.

    Article  PubMed  Google Scholar 

  • McIntire DD, Leveno KJ. Neonatal mortality and morbidity rates in late preterm births compared with births at term. Obstet Gynecol. 2008;111(1):35–41.

    Article  PubMed  Google Scholar 

  • Medlock S, et al. Prediction of mortality in very premature infants: a systematic review of prediction models. PLoS One. 2011;6(9):e23441.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Miller AR, Tucker CE. Can health care information technology save babies? J Polit Econ. 2011;119(2):289–324.

    Article  PubMed  Google Scholar 

  • Muglia LJ, Katz M. The enigma of spontaneous preterm birth. N Engl J Med. 2010;362(6):529–35.

    Article  CAS  PubMed  Google Scholar 

  • Padula M. Neonatal research network terminology harmonization: a formative research initiative of the national children’s study. National children’s study metadata repository workshop. 2012.

    Google Scholar 

  • Palma JP, et al. Neonatal informatics: computerized physician order entry. Neoreviews. 2011a;12:393–96.

    Article  PubMed  PubMed Central  Google Scholar 

  • Palma JP, et al. Impact of electronic medical record integration of a handoff tool on sign-out in a newborn intensive care unit. J Perinatol. 2011b;31(5):311–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Patrick SW, et al. Neonatal abstinence syndrome and associated health care expenditures: United States, 2000–2009. JAMA J Am Med Assoc. 2012;307(18):1934–40.

    Article  CAS  Google Scholar 

  • Patrick SW, et al. Increasing incidence and geographic distribution of neonatal abstinence syndrome: United States 2009 to 2012. J Perinatol. 2015;35(8):650–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Reidpath DD, Allotey P. Infant mortality rate as an indicator of population health. J Epidemiol Community Health. 2003;57(5):344–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Richards TB, et al. Geographic information systems and public health: mapping the future. Public Health Rep. 1999;114(4):359–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Rushton G, Lolonis P. Exploratory spatial analysis of birth defect rates in an urban population. Stat Med. 1996;15(7–9):717–26.

    Article  CAS  PubMed  Google Scholar 

  • Saigal S, Doyle LW. An overview of mortality and sequelae of preterm birth from infancy to adulthood. Lancet. 2008;371(9608):261–9.

    Article  PubMed  Google Scholar 

  • Schoendorf KC, Branum AM. The use of United States vital statistics in perinatal and obstetric research. Am J Obstet Gynecol. 2006;194(4):911–5.

    Article  PubMed  Google Scholar 

  • Seligman NS, et al. Relationship between maternal methadone dose at delivery and neonatal abstinence syndrome. J Pediatr. 2010;157(3):428–33. 33 e1.

    Article  CAS  PubMed  Google Scholar 

  • Shapiro-Mendoza CK, et al. Risk factors for neonatal morbidity and mortality among “healthy,” late preterm newborns. Semin Perinatol. 2006;30(2):54–60.

    Article  PubMed  Google Scholar 

  • Shortliffe EH. Biomedical informatics in the education of physicians. JAMA. 2010;304(11):1227–8.

    Article  CAS  PubMed  Google Scholar 

  • South AP, et al. Spatial analysis of preterm birth demonstrates opportunities for targeted intervention. Matern Child Health J. 2012;16(2):470–8.

    Article  PubMed  Google Scholar 

  • Spitzmiller RE, et al. Amplitude-integrated eeg is useful in predicting neurodevelopmental outcome in full-term infants with hypoxic-ischemic encephalopathy: a meta-analysis. J Child Neurol. 2007;22(9):1069–78.

    Article  PubMed  Google Scholar 

  • Task Force on Sudden Infant Death, Syndrome, R. Y. Moon. Sids and other sleep-related infant deaths: expansion of recommendations for a safe infant sleeping environment. Pediatrics. 2011;128(5):1030–9.

    Article  Google Scholar 

  • Thornton SN, et al. Neonatal Bilirubin management as an implementation example of interdisciplinary continuum of care tools. AMIA Annu Symp Proc. 2007:726–30.

    Google Scholar 

  • United Nations, Department of Economic and Social Affairs, Population Division. World population prospects: the 2010 revision, Cd-Rom Edition. 2011.

    Google Scholar 

  • United States Census Bureau. American Community Survey (Acs). 2016. Accessed 2 Mar 2016. Available from: https://www.census.gov/programs-surveys/acs/.

  • United States Environmental Protection Agency. Airdata. 2016. Accessed 2 Mar 2016. Available from: http://www.epa.gov/airdata/.

  • Vinikoor LC, et al. Reliability of variables on the North Carolina birth certificate: a comparison with directly queried values from a cohort study. Paediatr Perinat Epidemiol. 2010;24(1):102–12.

    Article  PubMed  PubMed Central  Google Scholar 

  • Wachman EM, et al. Association of oprm1 and comt single-nucleotide polymorphisms with hospital length of stay and treatment of neonatal abstinence syndrome. JAMA. 2013;309(17):1821–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Wachman EM, et al. Epigenetic variation in the Mu-Opioid receptor gene in infants with neonatal abstinence syndrome. J Pediatr. 2014;165(3):472–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Wachman EM, et al. Variations in opioid receptor genes in neonatal abstinence syndrome. Drug Alcohol Depend. 2015.

    Google Scholar 

  • Wang ML, et al. Clinical outcomes of near-term infants. Pediatrics. 2004;114(2):372–6.

    Article  PubMed  Google Scholar 

  • Wang H, et al. Global, regional, and national levels of neonatal, infant, and under-5 mortality during 1990–2013: a systematic analysis for the global burden of disease study 2013. Lancet. 2014;384(9947):957–79.

    Article  PubMed  PubMed Central  Google Scholar 

  • Wexelblatt SL, et al. Universal maternal drug testing in a high-prevalence region of prescription opiate abuse. J Pediatr. 2015;166(3):582–6.

    Article  PubMed  Google Scholar 

  • Wier ML, et al. Gestational age estimation on United States livebirth certificates: a historical overview. Paediatr Perinat Epidemiol. 2007;21 Suppl 2:4–12.

    Article  PubMed  Google Scholar 

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Authors and Affiliations

  1. Departments of Pediatrics and Biomedical Informatics, Perinatal Institute and Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, University of Cincinnati College of Medicine, 3333 Burnet Ave, ML 7009, Cincinnati, OH, 45229-3039, USA

    Eric S. Hall Ph.D.

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Correspondence to Eric S. Hall Ph.D. .

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Editors and Affiliations

  1. Children's Hospital Research Foundation, Cincinnati, Ohio, USA

    John J. Hutton

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Hall, E.S. (2016). Informatics for Perinatal and Neonatal Research. In: Hutton, J. (eds) Pediatric Biomedical Informatics. Translational Bioinformatics, vol 10. Springer, Singapore. https://doi.org/10.1007/978-981-10-1104-7_8

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